Local Coding Agent MCP server

Local Coding Agent

<!-- mcp-name: io.github.pvnc228/local-coding-agent -->

Local execution and safety layer for delegating coding tasks from cloud agents to models on your own machine.

What is Local Coding Agent?

Local Coding Agent lets a cloud coding agent delegate a narrow task to a local model without giving that model unrestricted access to your repository. Connect Codex, Claude Code, Cursor, Windsurf, Cline, OpenCode, Antigravity, or another compatible harness through MCP, the reusable Agent Skill, or the local-agent CLI. The cloud agent stays in charge of the larger task; Local Coding Agent supplies the controlled local execution path.

The calling agent sends a focused goal, a workspace, an allowlist of files, and checks. Your local model returns a proposal for review. The local model proposes; the controller verifies. A change is only reported as applied after the declared file scope held, the patch passed static analysis, and a real external test runner confirmed the configured checks. If a post-apply check fails, the change is rolled back and the rollback is itself verified against recorded file digests. The local model does not receive unrestricted shell or write access to your workspace.

Use the Desktop Harness when you want a Windows interface for local chat, model selection, sessions, task status, and change review. Use the CLI for terminals, scripts, CI, or direct integration with a coding harness. Both use the same controller and safety rules.

You keep control of Git and delivery. Local Coding Agent does not create commits, push branches, publish releases, or download a model on its own.

What the gate refuses

The same gate backs apply_proposal, local-agent apply, and the desktop apply action:

• A patch that touches a file outside the declared scope is rejected before the workspace is touched (error.kind: patchoutsidescope).
• An apply with no targeted check is refused — no external evidence, no apply (error.kind: applyrequireschecks).
• A patch that fails the post-apply checks is rolled back; the result is "rejected" with error.kind: postapplycheck_failed.
• A rollback that cannot be confirmed against the recorded baseline is reported as workspacemodified: true with workspacestate: "unknown" and risk kind rollback_failed — never as a clean restore.

Choose your download

Current public release: v1.1.1

Choose the CLI release for terminal workflows, scripts, CI, or integration with another AI coding environment. It provides the local-agent command, MCP server, Agent Skill, diagnostics, sessions, model tools, and task delegation.

Download the CLI wheel or CLI source archive. Windows users can download the Desktop Harness installer and verify the published files with SHA256SUMS.txt.

The v1.1.1 release contains the CLI archives and the Windows Desktop Harness installer. Local inference remains local; install Ollama or run a compatible local model server before requesting live model responses.

Desktop Harness

Shortened. The full README is on GitHub.